Cognitive Modifiability and Cognitive Functions
Cognitive Modifiability and Cognitive Functions
Oon-Seng Tan and Alice Seok-Hoon Seng
This chapter summarizes the theoretical bases of cognitive modifiability and cognitive functioning and how the effects of cognitive modifiability on cognitive functioning are supported empirically from several research studies that point to more positive results than otherwise thought so.
The key idea of cognitive modifiability came from Feuerstein's concept of structural cognitive modifiability (Feuerstein & Rand, 1990). His concept is best illustrated by his theory of structural cognitive modifiability (SCM), which states that “all human characteristics, including personality, cognition and behavior are modifiable states, regardless of etiology, age, or severity of the condition” (p. xxv).
In the first edition of the Learning Potential Assessment Device (LPAD) book by Feuerstein and his colleagues (Feuerstein 1979), the concept of modifiability was discussed in terms of a well defined population
whose adaptability was impaired by its low level of functioning. Impairment was viewed irrespective of etiological determinants—cultural difference, cultural deprivation, educational or socioeconomic conditions, and other factors—the common denominator being the inability to respond to the demands of adaptation required by society. This limitation has proved to be overly restrictive in that individuals with higher levels of functioning also need to learn how to learn and adapt themselves by modifying their cognitive structures, their strategies of functioning, and their ways of thinking. (Feuerstein et al., 2002)
According to the theory of structural cognitive modifiability, teaching thinking goes beyond dealing with tools and skills and entails addressing the entire cognitive structure. Modification and diversification of cognitive structure affect one's capacity to learn and to adapt to complex situations (Feuerstein et al., 1991). The theory believes in the plasticity and modifiability of cognition and suggests that by changing the total cognitive structure rather than selected dimensions of behavior a more enduring and stable state of modifiability can be achieved.
Embedded in the theory of SCM is the theory of mediated learning experience (MLE) that emphasizes the role of intentional human mediation and the quality of the interactive environment. Mediation plays a pivotal role in the cognitive development of the individual. According to Kozulin and Lurie (1994) and Kozulin (1998), mediated learning experience (MLE) as a determinant of cognitive development represents an advancement of cognitive theories. More importantly, MLE provides the theoretical basis for the reversibility of deficient cognitive processes under specified conditions of intervention. An effective intervention would depend not only on the design of the instrument or lessons but more importantly characteristics of the mediation process.
Another important area addressed by Feuerstein (1990) in relation to the theory of SCM is the need to understand what is going on in the mind of the learner by identifying what he refers to as “deficient cognitive functions.” An example of deficient cognitive function is “unplanned, impulsive, and unsystematic exploratory behavior.” Deficient functions could be conceived of as the result of a lack of mediated learning experience. The concept of cognitive functions relates to and helps identify the prerequisites of thinking.
The purpose of highlighting these functions is to emphasize the importance of the prerequisites of thinking in relation to the capacity of the learner to benefit from learning opportunities. Mehl (1985) worked with first-year university physics students and analyzed their cognitive difficulties. He concluded that valuable insights into understanding learning difficulties were gained through dealing with specific functions such as visualization of physical situation, qualitative evaluation of a problem, use of sketches, identification of implicit data, goal and problem analysis, elaboration of information, impulsivity and simultaneous handling of data.
Strang and Shayer (1993) observed that the cognitive functions approach provided the teacher with “insight into the cognitive difficulties associated with particular concepts so that these can be compensated for in the selection of materials and in the teaching approach adopted” (p. 336). As Skuy and Mentis (1991) noted, Feuerstein's criteria for MLE and his list of cognitive dysfunctions (e.g., impulsivity, episodic grasp of reality, need for accuracy) are two key dimensions for an intervention program. They noted that Feuerstein's checklist for cognitive functions and dysfunctions enables one to gain insights into his/her own cognitive skills and thus move to a level of reflective thinking and metacognition.
When he reviewed Feuerstein's work, Sternberg (1985b) noted that “the center of Feuerstein's (1980) theory is his listing of deficient functions” (p. 221). Sternberg (1985a) developed a componential approach in his Triarchic Theory of Intelligence. According to Sternberg, “a component is an elementary information process that operates upon internal representations of objects or symbols” (p. 97). The basic idea of components in Sternberg's theory is that they represent latent abilities of some sort that give rise to individual differences manifested in measures of intelligence or real-world performance. Sternberg classified components on the basis of their functions into metacomponents (e.g., planning and decision making), performance components (e.g., execution of a working strategy, comparing solutions obtained) and knowledge-acquisition components (e.g., obtaining new information).
Both Sternberg and Feuerstein have in common an information-processing orientation in their approaches. Some insights can be gained from comparing these approaches. Both approaches employ the use of components in terms of cognitive functioning although from somewhat different perspectives and methods of categorization. It can be argued that some unit of analysis is needed to understand cognitive functioning and performance. Rather than relying on psychometric approaches, Feuerstein and Sternberg provided models based on a wealth of clinical and empirical data respectively. As Sternberg (1985a) noted, “it would be a useful task to explore how the two theories might inform each other and be somehow combined into a more powerful unified theory” (p. 231). The implications of the above arguments are that (1) the identification of components of cognitive functions provides a valuable map for the design of an intervention as well as a diagnostic approach;and (2) there appear to be several advantages that can be reaped from both approaches in the combination of the scope of cognitive functions and components addressed, and the use of MLE to bring about cognitive modification.
Perkins (1985) and Sternberg (1986) reviewed the work of Feuerstein (Feuerstein, Rand, Hoffman & Miller, 1980) and observed that it provided hopeful signs of positive effects in the development of a number of cognitive abilities. Feuerstein et al. (1980) expounded a theory of cognitive modifiability with the principles and technology for intervention that has been described as one of the most “original … in scope, in theoretical importance, and in potential social significance” (Hobbs, 1980, p. 566).
The effectiveness of Feuerstein's Instrumental Enrichment (FIE) for regular school adolescents is supported by studies such as Ruiz and Castaneda (1983), Genasci (1983), Livingston (1988), Offenberg (1992) and Wilson (1994). Tan, Seng, and Foong (2005) found that intervention using adaptations of FIE improve several aspects of cognitive functions for secondary school students. Genasci (1983) and Skuy, Mentis, Arnott, and Nkwe (1990) also found that high-achieving and gifted adolescents were able to benefit from FIE. Mehl (1985), Martin and Jonas (1988) and Martin (1993) indicated that SCM interventions were in fact applicable to post-secondary and college students. The possibility of applying SCM interventions to adult populations is supported by studies such as Kozulin and Lurie (1994) and Rosen (1995). Kozulin and Lurie (1994) found that SCM was effective for educated immigrants in the age range of 27–50. Oliveira and Lau (1991) pointed out that FIE had been used in training people in industries in France and Switzerland.
Most studies used intelligence tests for assessing cognitive abilities. The Primary Mental Abilities (PMA) tests were used in studies such as Feuerstein and Rand (1977), Haywood, Tzuriel, and Vaught (1992) and Genasci (1983). The PMA scales assess verbal abilities, numerical abilities, spatial relations, reasoning (figure and word grouping), and perceptual speed factors. Studies like Haywood et al. (1982), Offenberg (1992), Martin and Jones (1988), and Kozulin and Lurie (1994) employed the Raven Matrices, which measure nonverbal intelligence. The Lorge-Thorndike tests were used in studies such as Ruiz and Castaneda (1983) and Haywood et al. (1982). The Lorge-Thorndike tests assess nu-merical abilities and nonverbal abilities such as figure classification and analogies. Mulcahy (1993) used the Cognitive Abilities Tests, which are similar to the Lorge-Thorndike tests in many ways and assess quantitative abilities, nonverbal abilities, and verbal abilties. Livingston (1988) and Wilson (1994) employed different intelligence tests but essentially used measures of verbal abilities and numerical abilities, and nonverbal intelligence tests. Hence the studies were generally concerned with the effects of SCM on quantitative abilities, verbal abilities, and nonverbal abilities (particularly fluid intelligence).
A diversity of measures were used for attitudes (affective-motivational factors). Factors that were appraised included areas such as motivation for learning, confidence, self-concept, locus of control, anxiety, and social skills. In the case of academic performance, citywide tests and school test results were generally employed.
It is not surprising that most studies concentrated on cognitive effects since SCM deals primarily with structural changes in cognition. A “broad brush” approach, rather than a meta-analysis of the size of the effects, is taken to see the trends from the studies reviewed.
Table 1.1 summarizes the effects of SCM for a number of studies that were conducted between 1997 to 2005. In the table the term “positive effects” is used when the studies showed that statistically significant gains were found. The term “probable effects” is used if the studies relied primarily on qualitative reporting and the term “not investigated” is indicated if the findings were not reported or investigated in the studies.
The trend indicated that most effects were actually on cognitive abilities. The effects on affective factors appeared to be more tenuous and the effects on academic achievement, if they were investigated, were often limited.
IMPLICATIONS FOR DYNAMIC ASSESSMENT
Given our understanding of modifiability we are primarily concerned with learning potential and untapped capacity. We would like to see every assessment as a learning opportunity for students, unlike static assessment and educational measurements that tend to measure manifest performance. Based on the evidence for modifiability, we take a perspective of assessment where there is interaction and active intervention. This dynamic approach makes assessment a learning experience interwoven with a diagnostic approach as well as intervention of the learner's cognitive functions.
The review of literature indicates that a model of SCM intervention should encapsulate the following key areas (Tan & Seng, 2005):
- Belief System. The modifiability of intelligence as the underpinning belief system of both the teacher (mediator) and the learner with emphasis on affective-motivational processes.
- Mediated Learning Experience (MLE). The focus on mediation with the deployment of key MLE parameters and a repertoire of mediated learning.
- Cognitive Functions. The identification of areas of cognitive focus and addressing prerequisites of thinking and development of higher order thinking.
TABLE 1.1 Effects of SCM interventions on cognitive abilities, attitudes, and academic performance. Study Effects of SCM Cognitive Abilities Attitudes Academic Performance Feuerstein and Rand (1977)
- Positive effects on mental abilities such as numerical abilities, spatial relations and figure grouping, and specific cognitive performance such as spatial orientation, rapidityprecision, concept formation.
- Long-term effects on intellectual ability.
- Positive effects on criteria such as self-sufficiency, adaptiveness, interpersonal conduct.
- No effects on factors such as motivation for learning and confidence in personal success
Positive effects on 2 out of 12 achievement tests. The areas were bible knowledge and geometry. Ruiz and Castaneda (1983); Ruiz (1985a)
- Positive effects on general intelligence, figure classification, figure analogies, and recognition of number series.
- Long-term effects on intellectual ability.
Positive effects on self-concept. Not investigated. Ruiz (1985b) Positive effects on general intelligence. Not investigated. Not investigated. Genasci (1983) Positive effects on mental abilities such as verbal abilities. No effects on affective factors. Not investigated. Livingston (1988) Probable effects on cognitive abilities on field dependents. Not investigated. No effects on science-process skills. Martin and Jonas (1988) Positive effects on logical reasoning. Not investigated. Positive effects on math concepts, math computation, and reading comprehension. TABLE 1.1 Effects of SCM interventions on cognitive abilities, attitudes, and academic performance. Study Effects of SCM Cognitive Abilities Attitudes Academic Performance Wood (1989) Not investigated.
- Positive effects on self-testing, information processing, and test strategies.
- No effects on factors such as attitude, motivation, time management, anxiety, and concentration.
No effects on mathematics examination scores and passing rates. Skuy et al. (1990) Positive effects on creative abilities in terms of fluency, flexibility and originality of thought. Probable effects on self-esteem and social skills. Not investigated. Blagg (1991) No effects on cognitive abilities. No effects on affective factors. No effects on attainment measures. Offenberg (1992) Positive effects on non-verbal intelligence. Not investigated.
- Positive effects on report card measures of English, reading,
- science, and social studies. No effects on citywide tests.
Mulcahy (1993) Positive effects on cognitive abilities in terms of verbal abilities, nonverbal intelligence, and quantitative abilities. Positive effects on affective perceptions such as perceived competence, self-concept, and locus of control. Positive effects on academic achievements such as reading and mathematics. Martin (1993) Probable effects on improvement in thinking patterns, and in being more systematic and reflective. Reported changes in self-perception and belief system. Not investigated. TABLE 1.1 Effects of SCM interventions on cognitive abilities, attitudes, and academic performance. Study Effects of SCM Cognitive Abilities Attitudes Academic Performance Strang and Shayer (1993) Probable effects on cognitive abilities. Not investigated. Probable effects on achievement in chemistry. Wilson (1994) Positive effects on visual motor integration abilities. Positive effects on perception of competency such as global selfworth, scholastic competence, and behavioral conduct. No effects on school achievement. Kozulin and Lurie (1994) Alleviation of cognitive difficulties previously identified. Positive effects on enhancing cognitive abilities. Not investigated. Not investigated. Rosen (1995) Probable effects on habits and patterns of thinking. Probable effects on perceptions of competence and success in work. Not investigated. Tan (2000) Positive effects on overall cognitive abilities, particularly quantitative abilities, and non-verbal intelligence. Positive effects on attitudes and motivation. No effects on academic achievement. Tan, Seng & Foong (2005) Positive effects on specific cognitive functions such as planning. Not investigated. Not investigated.
- Instruments for Intervention. The employment of cognitive tools, exercises, and activities for a diagnostic, dynamic assessment and active modification approach in conjunction with a cognitive map.
- Bridging. An emphasis on bridging to transfer and apply learning across situations. This includes transfer for learning to learn, acquisition of life skills, and content learning.
Dynamic assessment (DA) hypothesizes that cognitive deficiencies are attributable to a lack of cognitive intervention. To bring about structural cognitive modification, the theory of SCM suggests that intervention should address two areas, namely, MLE and cognitive functions. Mediated learning experience and cognitive functioning form two important foci for developing our intervention. Tan, Parson, Hinson, and Sardo-Brown (2003, p. 61) refined the original list of parameters by Feuerstein and Feuerstein (1991) and represented it as a repertoire. Mediated learning experience is emphasized through a Repertoire of Mediated Learning (RML), which is shown in Figure 1.1. The acronym IR-ME-T is a convenient way to remind the mediator that intentionality-reciprocity (IR), mediation of meaning (ME) and transcendence (T) are necessary and sufficient conditions at the core of MLE.
The theory of MLE is complemented by a theory of cognitive functioning that provides a map for identifying and focusing on cognitive dysfunctions and the prerequisites of thinking. Cognitive functions refer to what is going on in the mind of the learner and the domains of thinking we seek to improve. Figure 1.2 illustrates a list of cognitive functions that was drawn up. Referred to as the cognitive functions disc (CFD), the purpose is to highlight the three Cs of the input, elaboration and output phases of a mental act: (1) collecting information relates to the input phase; (2) connecting information and creating relationships relate to elaboration; and (3) communicating information relates to the output phase. Represented as a rotating annulus, a range of cognitive functions may relate to each of these phases.
With reference to the model in Figure 1.1, the next major component of the DA model is “bridging.” The RML represents the locus of parameters for the mediator intervention and bridging activities. The
awareness of these parameters (i.e., what is in the mind of the mediator) enables the mediator to emphasize connection between specific cognitive functions in the learner (i.e., the mind of the learner) and the environment for learning and adaptation to happen in day to day activities.
The awareness of the cognitive processes and strategies gained is then bridged through applications and examples to enable transfer of learning to (1) learning to learn; and (2) life skills and acquisition of course skills and content. When cognitive modifiability was studied among polytechnic students, bridging was emphasized as abilities to
handle college life and to meet the demands of the kinds of life-skills emphasized in today's world of fast-paced change.
Cognitive modifiability that is supported by developments in neuro-science and the theoretical foundation rooted in the works of Feuerstein as well as complemented by modern theories of intelligence such as the works of Sternberg appears to be promising. It is important to develop a model of dynamic assessment with components of (1) belief system and affective-motivational processes; (2) MLE and design of learning environment; (3) addressing of cognitive functioning; (4) instruments for intervention; and (5) bridging.
Dynamic assessment should include (1) an interactionist approach of the meeting of the minds of the teacher and learner; (2) the use of a diagnostic approach, dynamic assessment and active modification in conjunction with RML and the cognitive map; and (3) the emphasis on transfer to learning to learn, life skills and content learning. The idea of dealing with the prerequisites of thinking has much to do with the concept of modifiability in Feuerstein's theory (Feuerstein et al., 1980) where an intervention is aimed not merely to remediate specific behaviors and skills but to produce “changes of a structural nature.” Indicators of structural cognitive change include changes in cognitive abilities and attitudes. In other words the DA attempts to address the issue of helping students learn how to learn.
The emphasis on understanding the prerequisites of thinking (i.e., dealing with cognitive functions) and the kinds of environment for mediating cognitive development calls for teacher-education and staff development. There is a need to train teachers in the theory and philosophy of SCM and the use of DA. In fact the importance of MLE, of understanding cognitive functioning, and of ensuring effective affective-motivational processes provides a rationale for investment in staff development to empower teachers to be effective cognitive coaches and designers of the learning environment. Evaluation of the program should include both quantitative and qualitative studies.
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